I am trying to reverse a directed graph and to write the adjacency list of each vertex to a text file in the format
NodeId \t NeighbourId1,NeighbourId2,...,NeighbourIdn
So far I've only tried printing my output which is as follows:
(4,[J@13ad83aa)
(0,[J@338ff780)
(1,[J@6737f62b)
(3,[J@1250d788)
(2,[J@6d1fa6bb)
Whereas it should be of the format:
4 2
0 4
1 0,2
3 1,2,3
2 0,1
The current code I've been using is
object Problem2{
def main(args: Array[String]){
val inputFile:String = args(0)
val outputFolder = args(1)
val conf = new SparkConf().setAppName("Problem2").setMaster("local")
val sc = new SparkContext(conf)
val graph = GraphLoader.edgeListFile(sc,inputFile)
val edges = graph.reverse.edges
val vertices = graph.vertices
val newGraph = Graph(vertices,edges)
val verticesWithSuccessors: VertexRDD[Array[VertexId]] =
newGraph.ops.collectNeighborIds(EdgeDirection.Out)
val successorGraph = Graph(verticesWithSuccessors, edges)
val res = successorGraph.vertices.collect()
val adjList = successorGraph.vertices.foreach(println)
I don't think mkString()
can be used with a graph object. Is there a similar method for graph objects to get the string?
Let's take again this example:
val vertices: RDD[(VertexId, String)] =
sc.parallelize(Array((1L,""), (2L,""), (4L,""), (6L,"")))
val edges: RDD[Edge[String]] =
sc.parallelize(Array(
Edge(1L, 2L, ""),
Edge(1L, 4L, ""),
Edge(1L, 6L, "")))
val inputGraph = Graph(vertices, edges)
val verticesWithSuccessors: VertexRDD[Array[VertexId]] =
inputGraph.ops.collectNeighborIds(EdgeDirection.Out)
val successorGraph = Graph(verticesWithSuccessors, edges)
Once you have this:
val adjList = successorGraph.vertices
You can translate into a DataFrame easily:
val df = adjList.toDF(Seq("node", "adjacents"): _*)
df.show()
+----+---------+
|node|adjacents|
+----+---------+
| 1|[2, 4, 6]|
| 2| []|
| 4| []|
| 6| []|
+----+---------+
Now it's easy to transform with columns. Here a not so pretty example:
val result = df.rdd.collect().map(l=> l(0).asInstanceOf[Long] + "\t" + l(1).asInstanceOf[Seq[Long]].mkString(" "))
result.foreach(println(_))
1 2 4 6
2
4
6
Or also you can try with UDFs or handle the columns as you want.
Hope this helps!